IDEAS home Printed from https://ideas.repec.org/a/ags/asagre/338264.html
   My bibliography  Save this article

Relationship between Vegetation Index and Forest Surface Fuel Load in UAV Multispectral Remote Sensing

Author

Listed:
  • ZHOU,Yufei
  • WANG,Zhenshi
  • ZHONG,Yingxia
  • LI,Qiang
  • WEI,Shujing
  • LUO,Sisheng
  • WU,Zepeng
  • DAI,Ruikun
  • LI,Xiaochuan

Abstract

[Objectives] To explore the relationship between vegetation index and forest surface fuel load. [Methods] UAV multispectral remote sensing was used to obtain large-scale forest images and obtain structural data of forest surface fuel load. This experimental area was located in Gaoming District, Foshan City, Guangdong Province. The average surface fuel load of the experimental area was as high as 39.33 t/ha, and the forest surface fuel load of Pinus elliottii was the highest. [Results] The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) had moderately strong correlation with the forest surface fuel load. The regression model of NDVI (X) and forest surface fuel load (Y) was established: Y = -5.935 4X + 8.466 3, and the regression model of EVI (X) and forest surface fuel load (Y) was established: Y = -5.848 5X + 6.727 1. The study also found that the linear relationship between NDVI and surface fuel load was more significant. [Conclusions] Both NDVI and EVI have moderately strong correlations with forest surface fuel load. NDVI is moderately or strongly correlated with the surface fuel load of Pinus massoniana forest, shrub grassland, broad-leaf forest and bamboo forest, while EVI is only strongly correlated with surface fuel load of broad-leaf forest and bamboo forest. It is expected that the relationship between other vegetation indices and forest surface fuel load can be obtained by the method in this study, so as to find a more universal vegetation index for calculating surface fuel load.

Suggested Citation

  • ZHOU,Yufei & WANG,Zhenshi & ZHONG,Yingxia & LI,Qiang & WEI,Shujing & LUO,Sisheng & WU,Zepeng & DAI,Ruikun & LI,Xiaochuan, 2022. "Relationship between Vegetation Index and Forest Surface Fuel Load in UAV Multispectral Remote Sensing," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 14(10), October.
    • Handle: RePEc:ags:asagre:338264
    DOI: 10.22004/ag.econ.338264
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/338264/files/9.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.338264?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    Agribusiness;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:asagre:338264. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.